$11.50 - $15.50/hr
... AI, and related concepts. * Explain how data collection, annotation, labeling decisions, model ... Benefits: * Remote work: Work remotely from Romania or another location compatible with the ...
$11.50 - $15.50/hr
... AI, and related concepts. * Explain how data collection, annotation, labeling decisions, model ... Benefits: * Remote work: Work remotely from Romania or another location compatible with the ...
Senior SAR Imagery Scientist
Saint Louis, MO · Remote
$190K - $235K/yr
This role blends remote sensing science with applied data engineering and AI. What You'll Do ... Support annotation workflows by identifying and flagging imagery containing objects of interest
Senior SAR Imagery Scientist
Saint Louis, MO · Remote
$190K - $235K/yr
This role blends remote sensing science with applied data engineering and AI. What You'll Do ... Support annotation workflows by identifying and flagging imagery containing objects of interest
Ai Annotation Remote information
What is an AI annotation remote job?
AI Annotation Remote jobs involve labeling, categorizing, or tagging data such as images, videos, text, or audio to train artificial intelligence and machine learning models. These tasks are typically performed from home using a computer and specialized annotation tools provided by employers or platforms. The work helps improve the accuracy of AI systems in areas like speech recognition, computer vision, and natural language processing. It is common for these positions to be part-time or contract-based, and attention to detail is essential for success in this field.
What are the key skills and qualifications needed to thrive as an AI annotation remote worker?
To thrive as an AI Annotation Remote Worker, you need strong attention to detail, data labeling accuracy, and familiarity with basic computer operations, often supported by a high school diploma or higher. Experience with annotation platforms, image/video labeling tools, and understanding of data privacy protocols are typically required. Excellent communication, time management, and the ability to follow detailed instructions help individuals excel in this role. These skills ensure high-quality, precise data labeling that directly impacts the effectiveness of AI models.
What are the most common challenges faced by remote AI annotation specialists, and how can they be effectively managed?
Remote AI annotation specialists often encounter challenges such as maintaining consistent data quality, managing repetitive tasks, and communicating effectively with geographically dispersed teams. To overcome these issues, it's important to establish clear annotation guidelines, participate in regular team check-ins, and use collaboration tools for feedback and support. Utilizing productivity techniques and taking scheduled breaks can also help maintain focus and accuracy throughout the workday.
What is the difference between Ai Annotation Remote vs Data Labeler?
| Aspect | Ai Annotation Remote | Data Labeler |
|---|---|---|
| Required Credentials | Basic computer skills, attention to detail | Basic computer skills, attention to detail |
| Work Environment | Remote, flexible hours | Remote or on-site, flexible hours |
| Industry Usage | AI development, machine learning projects | Data preparation, machine learning datasets |
| Search & Comparison Intent | Often compared for entry-level AI data tasks | Related role for data preparation tasks |
Ai Annotation Remote and Data Labeler roles share similar requirements and work environments, focusing on data annotation for AI systems. However, Ai Annotation Remote often emphasizes more specialized tasks within AI development, while Data Labeler roles may include broader data preparation activities. Both are suitable for remote work and require attention to detail, making them popular choices for those entering the AI industry.
What are the most commonly searched types of Ai Annotation jobs in Missouri?
The most popular types of Ai Annotation jobs in Missouri are:
What are popular job titles related to Ai Annotation Remote jobs in Missouri?
For Ai Annotation Remote jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Ai Annotation Remote jobs in Missouri look for?
The top searched job categories for Ai Annotation Remote jobs in Missouri are:
- Github Remote
- Remote Data Science Neuroscience
- Remote Manufacturing Data Scientist
- Junior International Data Scientist
- Remote Data Entry Paid Training
- Freelance Data Scientist Machine Learning
- Contract Machine Learning Data Scientist
- Executive Data Scientist Experimentation
- Remote Game User Research
- Remote Variant Curation Scientist
What cities in Missouri are hiring for Ai Annotation Remote jobs?
Cities in Missouri with the most Ai Annotation Remote job openings:
$11.50 - $15.50/hr
Full-time
Posted 11 days ago
Job description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Instructor: Machine Learning Data Associate based in Netherlands.
This is an opportunity to lead engaging, high-impact virtual learning experiences for diverse audiences developing skills in machine learning and AI data workflows. You will deliver live technical instruction in German while collaborating professionally in English with program and operations teams. The role combines technical expertise, instructional leadership, and the ability to make complex AI concepts practical and accessible. You will help learners understand how data labeling influences machine learning systems, generative AI, multimodal models, and applied AI workflows. Sessions may range from smaller groups to audiences of thousands of learners in a highly interactive online environment. You will also contribute to curriculum refinement and continuous course improvement. This is a part-time contract position with a remote setup and scheduled sessions aligned with the EST/CEST time zones.
Accountabilities
- Lead and facilitate live virtual classes for diverse learner groups, potentially ranging from 100 to more than 8,000 participants, while maintaining strong engagement and an effective learning environment.
- Deliver technical instruction in German on machine learning data workflows, generative AI, foundation models, prompt engineering, RAG, multimodal AI, responsible AI, and related concepts.
- Explain how data collection, annotation, labeling decisions, model training, evaluation, and deployment are connected, helping learners understand the downstream impact of their work.
- Manage virtual classroom dynamics, including Q&A, chat activity, pacing, learner engagement, and timely delivery of planned content.
- Adapt instructional approaches, explanations, and lesson pacing to accommodate learners with different backgrounds and levels of technical understanding.
- Prepare thoroughly for each lecture and ensure that technical content is delivered accurately, clearly, and in an accessible manner.
- Collaborate with program and operations teams in English to support smooth delivery, communicate updates, escalate issues, and maintain alignment on schedules and learner needs.
- Contribute to curriculum design and continuous improvement, including suggesting edits, refining lessons, and supporting the development of hands-on learning activities.
- Provide constructive feedback before and after sessions to strengthen course quality and learner outcomes.
- Maintain a professional, respectful, responsive, and empathetic presence when interacting with learners, colleagues, contractors, and guest speakers.
- Fluency in German sufficient to deliver all instruction and learner support professionally, combined with strong English proficiency for written communication, meetings, alignment, and issue escalation.
- Strong practical understanding of the machine learning lifecycle, including data collection, model training, evaluation, and deployment, with the ability to explain how labeling decisions affect model behavior and downstream outputs.
- Solid knowledge of generative AI and foundation models, including concepts such as pre-training, fine-tuning, reinforcement learning from human feedback (RLHF), and human feedback for model alignment.
- Hands-on experience with prompt engineering, including zero-shot, one-shot, and few-shot prompting, and the ability to teach learners how to interpret requirements, identify task constraints, and evaluate output quality.
- Working knowledge of Retrieval-Augmented Generation (RAG) and production AI workflows, including the ability to explain how to assess outputs for relevance, faithfulness, and groundedness.
- Understanding of multimodal and cross-modal AI, including how models process and generate text, images, audio, and video, and how these capabilities influence annotation and evaluation tasks.
- Knowledge of responsible AI, privacy, confidentiality, security, bias awareness, and transparency principles relevant to data labeling and AI workflows.
- Demonstrated experience delivering high-quality live virtual instruction, ideally to large and diverse audiences.
- Experience supporting technical curriculum development, lesson refinement, skills labs, or similar instructional content.
- Strong communication, presentation, empathy, adaptability, and classroom-management skills, with the ability to make complex technical concepts easy to understand.
- A positive and collaborative mindset, with strong attention to preparation, professionalism, responsiveness, and continuous improvement.
- Preferred: AWS Certified AI Practitioner (AIF-C01) certification or equivalent expertise, particularly experience aligning training content with certification domains and supporting exam readiness.
- Remote work: Work remotely from Romania or another location compatible with the required time zone.
- Part-time contract: Flexible engagement structured around scheduled instructional sessions and program needs.
- Virtual-first environment: Deliver impactful learning experiences entirely online using modern virtual classroom tools.
- High-impact teaching: Reach diverse learner populations and contribute to workforce development in AI and data.
- Professional collaboration: Work alongside program, operations, and instructional teams in an international environment.
- Curriculum involvement: Contribute ideas and expertise to the development and continuous improvement of technical training content.
- Potential schedule flexibility: Program dates and lecture times may be adjusted depending on program requirements and instructor availability.
- Inclusive environment: Participate in a learning culture focused on respect, accessibility, diversity, and equal opportunity.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
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